Saving & resuming runs

A long agent run can be interrupted — a crash, a deploy, a timeout, or just a user who closes the tab. Persistence lets you save a run's progress and pick it back up later, instead of starting over.

Saving progress automatically

Give the agent a store (somewhere to save state) and a run id (a name for this run). After every step, the agent saves a checkpoint:

from agentix import Agent, FileStore

agent = Agent(model=m, system_prompt="...", tools=[...], store=FileStore("./runs"))
outcome = await agent.run("Big multi-step task…", run_id="job-123")

FileStore saves to disk. MemoryStore keeps things in memory (handy for tests). You can also write your own store to save anywhere (a database, cloud storage) — it's a small interface.

Resuming

If a run stops partway, resume it later with the same id:

outcome = await agent.resume("job-123")

The agent reloads the conversation and continues from where it left off. This is also how human approval in web apps works — a run pauses, gets saved, and resumes once someone approves. See Cost, budgets & human approval.

→ Runnable example: examples/08_persistence.py